An EM Algorithm for Lebesgue-sampled State-space Continuous-time System Identification

被引：1

作者：

Gonzalez, Rodrigo A. ^{[1
]}

Cedeno, Angel L. ^{[2
,3
]}

Coronel, Maria ^{[3
]}

Aguero, Juan C. ^{[2
,3
]}

Rojas, Cristian R. ^{[4
]}

机构：

[1] Eindhoven Univ Technol, Dept Mech Engn, Eindhoven, Netherlands

[2] Univ Tecn Federico Santa Maria, Elect Engn Dept, Valparaiso, Chile

[3] Adv Ctr Elect & Elect Engn AC3E, Valparaiso, Chile

[4] KTH Royal Inst Technol, Div Decis & Control Syst, Stockholm, Sweden

来源：

IFAC PAPERSONLINE | 2023年 / 56卷 / 02期

基金：

瑞典研究理事会;

关键词：

System identification; continuous-time systems; event-based sampling; expectation-maximization; MODELS;

D O I：

10.1016/j.ifacol.2023.10.1771

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper concerns the identification of continuous-time systems in state-space form that are subject to Lebesgue sampling. Contrary to equidistant (Riemann) sampling, Lebesgue sampling consists of taking measurements of a continuous-time signal whenever it crosses fixed and regularly partitioned thresholds. The knowledge of the intersample behavior of the output data is exploited in this work to derive an expectation-maximization (EM) algorithm for parameter estimation of the state-space and noise covariance matrices. For this purpose, we use the incremental discrete-time equivalent of the system, which leads to EM iterations of the continuous-time state-space matrices that can be computed by standard filtering and smoothing procedures. The effectiveness of the identification method is tested via Monte Carlo simulations.

引用

页码：4204 / 4209

页数：6

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